Hi there! Thanks for your curiosity👋

If you are looking for a happy environment where you can exercise your creativity, sharpen your growth mindset and experiment, then scroll this down!

Who we are

Zubale is a technology company that enables retailers to win in eCommerce in Latin America. We partner with a wide range of retailers from supermarkets, specialty stores, pharmacies, department stores and fashion brands to help them win in eCommerce. How? We have three key products:

1) Flexifleet: Marketplace of freelancers to pick-pack-ship ecommerce orders

2) Ecommerce Fulfillment software

3) Client Engagement Suite software

We are obsessed with helping brands and retailers improve their eCommerce direct channels experience, reduce costs and improve EBITDA.

What You’ll Do:

• Design, build, deploy, maintain, and monitor scalable machine learning systems in production environments.
• Deliver high-impact products by integrating ML solutions seamlessly into user-facing applications or business processes.
• Implement and manage MLOps pipelines for continuous integration, continuous delivery (CI/CD), and automated retraining of ML models.
• Collaborate with product managers, data scientists, and engineers to translate business needs into ML-driven solutions.
• Optimize algorithms for performance, scalability, and cost-efficiency in production.
• Monitor and troubleshoot deployed models, ensuring stability, quality metrics, and robustness over time.
• Manage data workflows including ingestion, preprocessing, feature engineering, and validation.
• Document solutions, workflows, and system architectures for cross-team transparency and maintainability.
• Stay up to date with advancements in machine learning, optimization algorithms, and relevant frameworks to recommend and integrate best practices.
• Build and deploy AI Agent modules using ADK (Agent Development Kit) and integrate with MCPs (Model Context Protocol) to extend intelligent system capabilities.

What You Bring:

• Studies: Bachelor’s degree in Computer Science, Data Science, Mathematics, or a related field (Master’s or PhD preferred).
• Languages: Proficiency in Python (must) and understanding of SQL for data querying.
• Desired Tools:
• ML frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost, LightGBM.
• MLOps tools: MLflow, Kubeflow, Vertex AI, SageMaker, or similar.
• Deployment tools: Apache Airflow, Docker, Kubernetes, REST APIs, FastAPI, Flask, Jupyter Notebooks.
• Version control: Git/GitHub.
• Cloud platforms: GCP.
• Data tools: BigQuery, Postgres.
• Monitoring: Grafana, or equivalent.
• Visualization: Metabase, Superset, Pyplot, or similar.

Experiences:

• Deep understanding of machine learning and optimization algorithms.
• Proven track record of deploying ML models into production environments.
• Daily use of AI-assisted IDEs (e.g., Cursor, GitHub Copilot) integrated with AI Agents and MCPs.
• Hands-on experience with model lifecycle management and automated/planned retraining workflows.
• Understanding of software engineering best practices and CI/CD in ML systems.
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with monitoring model performance and diagnosing drift or degradation.

Nice to have:

• Experience with LLMs, chatbot solutions, and natural language processing.
• Exposure to deep learning architectures.
• Experience in routing, batching, assignment optimization.
• Experience in forecasting and recommendation systems.
• Exposure to big data ecosystems.
• Knowledge of experiment tracking and A/B testing for ML models.
• Familiarity with real-time inference systems.
• Contributions to open-source ML projects or research publications.